|
|
|
Registros recuperados: 12 | |
|
| |
|
|
Rodrigues,Tatiana P. N. da S.; Pandorfi,Héliton; Stosic,Borko; Lucena,Aline C. de; Rodrigues,Diogo F. B.. |
ABSTRACT The objective of this study was to develop a software based on image processing and computer vision techniques for monitoring the feeding/collective behavior of broilers (Cobb) and validate it based on the results obtained from the visual analysis of an expert. The visual analysis was performed based on the observation and quantification of behaviors in the interval of 10 min at each hour of the day, in the period of 24 hours, totaling 1728 frames/day, for males and females. The software was developed using the Hoshen-Kopelman algorithm, for labeling clusters, which would basically be the grouping of similar pixels. This software is written in the 1999 standard of the C language. After this stage of programming, the Hoshen-Kopelman algorithm... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Broiler farming; Image processing; Lighting system; Computer vision. |
Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162020000600657 |
| |
|
| |
|
| |
|
| |
|
|
Kazantzidis, Ioannis; Florez-revuelta, Francisco; Dequidt, Mickael; Hill, Natasha; Nebel, Jean-christophe. |
With the development of applications associated to ego-vision systems, smart-phones, and autonomous cars, automated analysis of videos generated by freely moving cameras has become a major challenge for the computer vision community. Current techniques are still not suitable to deal with real-life situations due to, in particular, wide scene variability and the large range of camera motions. Whereas most approaches attempt to control those parameters, this paper introduces a novel video analysis paradigm, ‘vide-omics’, inspired by the principles of genomics where variability is the expected norm. Validation of this new concept is performed by designing an implementation addressing foreground extraction from videos captured by freely moving cameras.... |
Tipo: Text |
Palavras-chave: Computer vision; Freely moving camera; Genomics; Foreground detection; Segmentation; Scanlines. |
Ano: 2018 |
URL: http://archimer.ifremer.fr/doc/00405/51643/52191.pdf |
| |
|
| |
|
|
Blay, Carole; Haffray, Pierrick; Bugeon, Jérôme; D’ambrosio, Jonathan; Dechamp, Nicolas; Collewet, Guylaine; Enez, Florian; Petit, Vincent; Cousin, Xavier; Corraze, Geneviève; Phocas, Florence; Dupont-nivet, Mathilde. |
One of the top priorities of the aquaculture industry is the genetic improvement of economically important traits in fish, such as those related to processing and quality. However, the accuracy of genetic evaluations has been hindered by a lack of data on such traits from a sufficiently large population of animals. The objectives of this study were thus threefold: (i) to estimate genetic parameters of growth-, yield-, and quality-related traits in rainbow trout (Oncorhynchus mykiss) using three different phenotyping technologies [invasive and non-invasive: microwave-based, digital image analysis, and magnetic resonance imaging (MRI)], (ii) to detect quantitative trait loci (QTLs) associated with these traits, and (iii) to identify candidate genes present... |
Tipo: Text |
Palavras-chave: Aquaculture; Fat content; Flesh colour; Magnetic resonance imaging; Fatmeter; Computer vision; Genetic correlations; QTL. |
Ano: 2021 |
URL: https://archimer.ifremer.fr/doc/00682/79410/81958.pdf |
| |
|
| |
|
|
Weber,Vanessa Aparecida de Moraes; Weber,Fabricio de Lima; Gomes,Rodrigo da Costa; Oliveira Junior,Adair da Silva; Menezes,Geazy Vilharva; Abreu,Urbano Gomes Pinto de; Belete,Nícolas Alessandro de Souza; Pistori,Hemerson. |
Abstract The objective with this study was to analyze the body measurements of Girolando cattle, as well as measurements extracted from their images, to generate a model to understand which measures further explain the cattle body weight. Therefore, the experiment physically measured 34 Girolando cattle (two males and 32 females), for the following traits: heart girth (HGP), circumference of the abdomen, body length, occipito-ischial length, wither height, and hip height. In addition, images of the dorsum and the body lateral area of these animals allowed measurements of hip width (HWI), body length, tail distance to the neck, dorsum area (DAI), dorsum perimeter, wither height, hip height, body lateral area, perimeter of the lateral area, and rib height.... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Cattle; Computer vision; Livestock precision; Machine learning; Mass estimation. |
Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982020000100800 |
| |
|
| |
|
| |
Registros recuperados: 12 | |
|
|
|